Digital Commons Network^™

Multiscale Modeling Of The Thermomechanical Behavior Of Polymeric And Molecular Organic Semiconductors, Kehinde H. Fagbohungbe

University of Kentucky Doctoral Dissertations

Organic semiconductors, derived from π-conjugated polymers and molecules, enable the development of deformable, stretchable and flexible electronics due to their tunable redox, optical, electronic and mechanical properties. However, an informed understanding of how multi-scale morphological characteristics of the polymeric and molecular semiconductors influence bulk properties that contribute to electronic and optical performance, especially under operational thermal and mechanical stresses, remains incomplete. This lack of understanding poses a challenge to scalability and commercialization of organic electronics. This dissertation develops and deploys computational modeling approaches, particularly atomistic molecular dynamics (MD) simulations, to investigate the multiscale morphological behavior of these synthetic semiconducting materials …

A Comprehensive Review Of Cyber Security And Current Practices In Global Mining Critical Infrastructure, Abu Barkat Ullah, Wanli Ma, Mohiuddin Ahmed, Bazlur Rashid, Munir Ahmad Saeed, Omer Arshad, Utkarsh Raghav

Research outputs 2022 to 2026

The purpose of the study is to explore the reasons behind the low uptake of Information Security Management Standards (ISMS), Asset Management, and Business Continuity Plans despite increasing cyber threats to the mining sector. Mining companies need to modernize and automate to keep up with the ‘Fourth Industrial Revolution’, driven by disruptive technology, forcing systems and technologies to become more integrated, increasing cyber attack threats. To address this, we conducted a literature review analyzing the mining industry across various regions. The research is based on a qualitative analysis of diversified literature. The results highlighted factors behind the low uptake of …

Designing An Approach To Developing Students' Symbol Sense For The Derivative In Calculus, Laura E. Weinstein

Theses, Dissertations and Culminating Projects

Students often struggle to connect the conceptual meaning of the derivative with the symbolic structures of Leibniz (dy/dx) notation. Although symbol sense has been described as the coordination of mathematical concepts, signs, and objects, little is known about how instruction can purposefully support students in developing symbol sense for the derivative. This study addresses this gap by designing and examining a learning approach aimed at helping students construct the relational structures underlying derivative notation. Using design research methodology, the study engaged intact algebra, precalculus and calculus classes in a suburban New Jersey high school across iterative cycles of design, implementation, …

Superelectrophile Promoted Synthesis Of Heterospirocycles, Mariam A. Adegbenro

Graduate Research Theses & Dissertations

Spirocycles are important scaffolds with a wide range of applications in material science as well as in medicine. The introduction of a heteroatom into the spirocyclic framework can improve its electronic, photophysical, and structural properties. Various reports have been published on the incorporation of atoms other than carbon into the spirocycle. The work outlined in this dissertation involves the development of synthetic methodologies for the synthesis of hetero-spirocycles via superacid-promoted cyclization reactions. These concepts are summarized in Chapter 1.

Chapter 2: Aromatic imines were prepared from 9-fluorenone and azafluorenones, and these substrates were reacted in the Brønsted superacid, triflic acid, …

All Games Have Equilibria, Arthur Paul Pedersen, M. Ali Khan, Maxwell B. Stinchcombe

Publications and Research

Research on Nash equilibrium existence for infinite games has grown into a patchwork of technical preconditions and counterexamples. This paper presents a unified program in equilibrium theory by revising the predominant model of mixed strategies based on countable additivity. A game is specified by a nonempty set of players and, for each player, a nonempty action set and a bounded von Neumann-Morgenstern utility function. Every such game is shown to admit a Nash equilibrium in finitely additive mixed strategies. In addition, the equilibrium correspondence for any such game is shown to be nonempty, compact-valued, and upper hemicontinuous, and the same …

From Authorization To Loss: A Blockchain Forensic Analysis Of Transaction-Level Mechanisms In Cryptocurrency Airdrop Scams, Chanwoo Shin, Kyung-Shick Choi

International Journal of Cybersecurity Intelligence & Cybercrime

Cryptocurrency airdrop scams have emerged as a rapidly growing form of cyber-enabled financial crime, yet remain underexplored in empirical research. This study examines how transaction-level mechanisms and offender strategies influence variation in monetary loss in airdrop scam incidents. Grounded in Cyber-Routine Activities Theory (Cyber-RAT), the study conceptualizes financial harm as occurring within decentralized environments where users’ online behaviors, particularly transaction authorization, intersect with limited digital capable guardianship. Data were drawn from 112 validated airdrop scam cases reported on Chainabuse.com between January and December 2025. Blockchain forensic analysis using Breadcrumbs was conducted to reconstruct transaction pathways, identify exchange interactions, and detect …

Serum Biomarker Trajectory Clusters Predict Functional Outcome And Quality Of Life For Traumatic Brain Injury, Thanh Son Do, Chantal Carnes, Zhihui Yang, Firas Kobeissy, Hamad Yadikar, Gayla R. Olbricht, Olli Tenovuo, Jussi P. Posti, Ewout W. Steyerberg, Lindsay Wilson, Nicole Von Steinbüchel, Endre Czeiter, Andras Buki, David K. Menon

Mathematics and Statistics Faculty Research & Creative Works

Serum brain-enriched biomarkers are increasingly employed in the clinical evaluation of traumatic brain injury (TBI) to assist with triage, neuroimaging decisions, and prognostication. However, the potential of temporal biomarker trajectories to inform disease monitoring and long-term outcomes remains underexplored. We aim to identify distinct biomarker trajectory (TRAJ) profiles in traumatic brain injury patients and to examine their associations with long-term clinical outcomes. The study included 373, CT-positive Intensive Care Unit (ICU) traumatic brain injury patients (256 with initial Glasgow Coma Scale 3–12) from the Collaborative European Neurotrauma Effectiveness Research in TBI (CENTER-TBI) core study who had at least two serum …

Shaping The Future: Emerging Technologies And Their Role In Industry 4.0 And Beyond, Liuliu Qin

Information Technology & Decision Sciences Faculty Publications

This paper provides a comprehensive review of emerging technologies driving the transition from Industry 4.0 to Industry 5.0. It examines the foundational concepts and pillars of Industry 4.0 and explores the transformative roles of Artificial Intelligence (AI), Extended Reality (XR), Collaborative Cobots (Cobots), Brain–Computer Interfaces (BCIs), quantum technologies, and next-generation connectivity (5G/6G). By integrating technological, human-centric, and sustainability perspectives, the study outlines how these emerging technologies reshape industrial systems and enable intelligent, adaptive, and inclusive futures.

Previsit Ai: A Retrieval-Augmented Generation For Patient Readiness In Clinical Encounters, Rolande Umuhoza

All Graduate Theses, Dissertations, and Other Capstone Projects

With healthcare systems under growing pressure from rising patient volumes and shrinking consultation windows, improving how patients communicate with physicians has become essential to delivering quality care. Yet patients routinely arrive at appointments unable to clearly describe their symptoms, recall their medical history, or articulate concerns, contributing to miscommunication, diagnostic inefficiency, and pre-visit anxiety. This study introduces PreVisit AI, a conversational system designed to address this gap through structured, knowledge-based patient preparation. The system is built on a Retrieval-Augmented Generation (RAG) architecture combining HuggingFace sentence embeddings (all-MiniLM-L6-v2), a Chroma vector store, and Google’s Gemini language model over a curated seven-document …

Vision-Language System Using Open-Source Llms For Consent And Instruction Gestures In Medical Interpreter Robots, Tung Ngo, Emma Murphy, Robert Ross

Conference papers

Effective communication is vital in healthcare, especially across language barriers, where non-verbal cues and gestures are critical. This paper presents a privacy-preserving vision-language framework for medical interpreter robots that detects specific speech acts (consent and instruction) and generates corresponding robotic gestures. Built on locally deployed open-source models, the system utilizes a Large Language Model (LLM) with few-shot prompting for intent detection. We also introduce a novel dataset of clinical conversations annotated for speech acts and paired with gesture clips. Our identification module achieved 0.90 accuracy, 0.93 weighted precision, and a 0.91 weighted F1-Score. Our approach significantly improves computational efficiency and, …

Regulating Ai Beyond Product Liability, Shruti Trikanad

Michigan Technology Law Review

Artificial Intelligence (AI) is being used by governments across the world to enforce regulatory mandates, adjudicate benefits and privileges, predict and analyze risks, and much more. Although this has significant potential to increase efficiency and responsiveness, it also comes with several risks of transparency, government accountability, and the amplification of discrimination and bias. It is crucial we oversee and regulate these AI systems effectively. This essay argues against the models that current regulatory frameworks are adopting to govern AI use: those resembling product liability.

Through the lens of the European Union's AI Act and Liability Directive, it highlights the unsuitability …

Toward Interpretable Multi-Omics Multimodal Biomedical Artificial Intelligence, Yanjun Lyu

Computer Science and Engineering Dissertations

The complexity of human disease arises from biological processes that unfold across multiple scales, from molecular variation through cellular function, tissue organisation, brain phenotypes, each of which is associated with distinct measurement modalities, regularities, and characteristic. Contemporary biomedical artificial intelligence has brought the opportunity to reveal the complexity with in; however, its methodological default, in which models are trained on most readily available modality, does not adequately engage with the multi-scale connected structure by which biological meaning is constituted. The research area of multi-omics and multi-modal AI for biomedicine remains at an early exploratory stage, and the work presented in …

Uncertainty Quantification, Propagation & Conjunction Assessment In Orbital Mechanics Using Generalized Polynomial Chaos Expansion & 2-Dimensional Conjunction Plane Analysis Techniques, Monalisa Karim

Mechanical and Aerospace Engineering Theses

Uncertainties, that are inherent to dynamic models, can be associated with state initial conditions, force modelling errors, navigation and actuation errors. In system modelling stochastic differential equations are used to represent dynamic phenomena with uncertainties, for which the solutions are probability density functions of quantities of interest characterizing the realization of the stochastic processes. In Polynomial Chaos Expansion (PCE) propagation, these solutions are represented as weighted sums of multivariate spectral polynomials that are functions of the input random variables. Generalized polynomial chaos expansion (gPC) is an extension to the original homogenous PCE which projects the random solution onto a basis …

Modeling Landslide-Generated Tsunami For Hazard Analysis: A Case-Study Of Grewingk, Ak, Cassidy J. Deer

All Master's Theses

Landslide-generated tsunamis pose an increasing hazard in glacial and paraglacial environments, where glacial retreat results in slope instability and the potential for mass movement events into a body of water. This thesis analyzes a landslide–generated tsunami at Grewingk Lake in October 1967 by integrating numerical simulations from the D-Claw and GeoClaw models, which are both derived from the Clawpack framework for solving hyperbolic conservation laws. By modeling landslide dynamics and wave propagation in a coupled manner, this study seeks to improve understanding of the hazard, risks and spatial impact at Grewingk. The D-Claw and GeoClaw modeling approaches complement each other …

Rydberg Atom Arrays For Electric Field Sensing, James P. Hamilton

Honors College Theses

Rydberg atoms, hydrogen-like atoms that can be excited to states of high principal quantum number that carry correspondingly large electric dipole moments, have become leading candidates for precision electric field sensing. Arrays of such atoms, each trapped in a focused laser beam called an “optical tweezer,” are a particularly promising platform, since the strong dipole-dipole interactions between neighboring atoms provide a resource unavailable in a single-atom sensor. This thesis develops a theoretical and numerical framework for electric field measurement in small Rydberg atom arrays. We begin with a two-level model of a single atom, derive the Hamiltonian and equations of …

The Effects Of Financing Green And Brown Sectors: What Do Theories And Evidence Say?, Hao Liang, Maria Teresa Punzi

Research Collection Lee Kong Chian School Of Business

This paper critically examines the economic and welfare implications of financing green and brown sectors. Drawing on a comprehensive review of recent theoretical and empirical literature, we highlight that while conventional green finance—allocating capital toward environmentally friendly (“green”) sectors and away from carbon-intensive (“brown”) sectors—can promote decarbonization, it may also produce unintended externalities. In particular, it can inadvertently incentivize higher emissions from brown firms and contribute to economic disruption. Using a dynamic stochastic general equilibrium (DSGE) model, we demonstrate that lowering the cost of capital for green sectors leads to only modest reductions in emissions, whereas raising it for brown …

Rrto: A High-Performance Transparent Offloading System For Model Inference In Mobile Edge Computing, Zekai Sun, Xiuxian Guan, Zheng Lin, Yuhao Qing, Haoze Song, Zihan Fang, Zhe Chen, Fangming Liu, Heming Cui, Wei Ni, Jun Luo

Research outputs 2022 to 2026

Deploying Machine Learning (ML) applications on resource-constrained mobile devices remains challenging due to limited computational resources and poor platform compatibility. While Mobile Edge Computing (MEC) offers an offloading-based inference paradigm using GPU servers, existing approaches can be divided into non-transparent and transparent methods, with the former necessitating source-code modifications. Non-transparent offloading achieves high performance but requires intrusive code changes, limiting compatibility with diverse applications. Transparent offloading, in contrast, offers wide compatibility but introduces two challenges: performance degradation under MEC's low and fluctuating bandwidth, where per-operator remote procedure calls (RPCs) inflate end-to-end latency and energy consumption; and black-box logic reconstruction, which …

Variational Autoencoder Inverse Mapper For Extraction Of Compton Form Factors: Benchmarks And Conditional Learning, Douglas Adams, Md Fayaz Bin Hossen, Joshua Bautista, Gia-Wei Chern, Simonetta Liuti, Marie Boër, Marija Čuić, Michael Engelhardt, Gary R. Goldstein, Huey-Wen Lin, Yaohang Li

Computer Science Faculty Publications

Deeply virtual exclusive scattering processes (DVES) serve as precise probes of nucleon quark and gluon distributions in coordinate space. These distributions are derived from generalized parton distributions (GPDs) via Fourier transform relative to proton momentum transfer. QCD factorization theorems enable DVES to be parameterized by Compton form factors (CFFs), which are convolutions of GPDs with perturbatively calculable kernels. Accurate extraction of CFFs from DVCS, benefiting from interference with the Bethe–Heitler (BH) process and a simpler final state structure, is essential for inferring GPDs. This paper focuses on extracting CFFs from DVCS data using a variational autoencoder inverse mapper (VAIM) and …

Open Scholarly Information Systems: Status Quo, Challenges, Opportunities, Hannah Bast, Guillaume Cabanac, Paolo Manghi, Jian Wu, Marcel R. Ackermann

Computer Science Faculty Publications

Over the past 30 years, a rich ecosystem of scholarly information systems has developed that openly provide their services to the scientific community. These systems include aggregators of bibliographic metadata (e.g., DBLP, OpenCitations, OpenAIRE Graph, OpenAlex, ORKG, Semantic Scholar, CiteSeerX, and CORE); publication, data, and software repositories (e.g., Arxiv.org, Figshare, Zenodo, Software Heritage, and Dataverse); and PID authorities (e.g., ORCID, ROR, Crossref, and DataCite). This interdisciplinary Dagstuhl Seminar "Open Scholarly Information Systems: Status Quo, Challenges, Opportunities" (25381) was the first of its kind to bring together practitioners from this ecosystem, as well as researchers investigating related questions or relying on …

Proof Of Recovery: A Model To Enhance Data Integrity In Data Management Systems, Gustaf Barkstrom

Theses and Dissertations

Businesses lose millions of dollars every year when they can’t restore data from backups. Research shows that Disaster Recovery Plan (DRP) testing is not conducted frequently enough, nor are records maintained that demonstrate full data recovery from backups. This work introduces a design science artifact called PRTOK that aims to increase DRP testing. The design science artifact is a software solution that integrates with Data Management Systems (DMS)

such as iRODS and DSpace, and can work with formats such as HDF5 and BagIt. Proof-of- recovery records, or tokens, are recorded in a replicated, resilient, and indelible proof-of- authority blockchain data …

Recirculated Submarine Groundwater Discharge Dominates Nutrient Inputs And Enhances Eutrophication Risk In A Coastal Lagoon, Júlia Rodriguez-Puig, Clara Ruiz-González, Marc Diego-Feliu, Irene Alorda-Montiel, Aaron Alorda-Kleinglass, Daniel Romano-Gude, Andrea G. Bravo, Júlia Dordal-Soriano, Javier Gilabert, Sophia Bergeler, Celine Lavergne, Gemma Casas, Marisol Manzano, Jordi Garcia-Orellana, Valentí Rodellas

OES Faculty Publications

Submarine groundwater discharge (SGD) is a widely recognized pathway for nutrient transport to coastal systems. Prior studies overlook the unique biogeochemical signatures of different SGD pathways, neglecting their differences in biogeochemical transformations and spatiotemporal factors. Here, we present an integrated assessment of nutrient delivery through three SGD pathways (fresh SGD, long‐scale recirculated SGD, and short‐scale porewater exchange), alongside surface water inputs, to evaluate their seasonality and impact on nutrient dynamics in a coastal lagoon. We conducted five field surveys in March, July, and November 2021, July 2024, and March 2025 in the Mar Menor lagoon, an ecosystem facing severe ecological …

Microbial Mats In Dinosaur Ichnocoenoses, Nora Noffke, Paul C. Murphy, Roger C. Buntin, Martin G. Lockley

OES Faculty Publications

Until now, the significance of microbial mats in preservation of dinosaur tracks and in reconstructing the palaeoenvironment in which dinosaurs roamed was rarely studied. Dinosaur tracks are commonly found close to ancient aquatic bodies where moist sediment had once allowed footstep registration. At such sites, epibenthic or endobenthic microbial mats may have developed as well and may have led to exquisite track preservation. Microbial mats in coastal, lacustrine or flood plain environments cause 'microbially induced sedimentary structures—MISS', which are micobialites found in sandy or evaporitic settings. The microbial structures record environmental parameters including meteorological conditions that existed at the time …

Efficient Preservation Of Old Methane-Derived Organic Carbon In Deep-Sea Surface Sediments, Rui Bao, Yangli Che, Mingzhi Liu, Naiyu Zhang, Yang Zhou, Lihua Dong, Shen Li, Owen A. Sherwood, Min Yu, Zongheng Chen, Shengxiong Yang, Nan Wang, Longhai Zhu, Jiawang Chen, Mutai Bao, Haoshuai Li, Luonan Chen, Weifeng Wu, Haiyue Ma, David J. Burdige

OES Faculty Publications

Methane released from the subseafloor is significantly attenuated during upward migration, yet the preservation of methane-derived organic carbon (OC) in global deep-sea sediments remains poorly understood. Here, we measured carbon isotopes coupled with temperature-ramped analyses on various methane seepage sediments. Our results reveal a correlation between the radiocarbon (¹⁴)C) content in deep-sea surface sediments and sulfate-methane transition depth. Notably, our findings suggest that a substantial amount of (¹⁴)C-depleted OC may originate from deep-seated methane and is efficiently preserved in surface seepage sediments. We propose that the efficient OC preservation is related to microbial-mediated aggregate formation at the seawater-sediment interface, where …

Visualizing The Barely Detectable: Particle Characteristics Of The Elusive Aquatic Gel Phase In The Northeastern Subtropical Atlantic, Huanqing Huang, María Couret, Santiago Hernández-León, Alexander B. Bochdansky

OES Faculty Publications

Marine gels constitute a large yet poorly explored ocean carbon pool. Shadow imaging was tuned to detect particles at two sensitivity levels: high–optical density particles (HODP), resembling the particles captured by most imaging systems, and low–optical density particles (LODP), representing a vastly more abundant and gel-dominated pool. This method enabled us to map and characterize a portion of oceanic gels without filtration and staining. In the subtropical northeast Atlantic, LODP outnumbered HODP of the same size by one or two orders of magnitude. Morphology and particle number spectra differed greatly between the two pools, with LODP showing greater morphological homogeneity …

Design Principles For Customer-Engaging Digital Service Systems: An Action Research Study, Keng Leng Siau, Xiaofeng Chen, Xin Tan

Research Collection School Of Computing and Information Systems

Digital services represent a business approach employed by organizations to operate in the digital environment. However, systematic development guidelines for developing quality digital service systems are lacking in the literature. The authors identified four general challenges for developing and implementing customer-engaging digital service systems (CEDSS). By employing the method of canonical action research in a digital service system project, they derived 10 design principles for developing high-quality CEDSS. They empirically evaluated the design principles in the development project and through follow-up focus group sessions. The design principles provide applicable and actionable guidelines for the development of CEDSS.

Hope Is An Act, Not A Wish: An Autoethnographic Journey Of Reimagining Disability As A Catalyst For Playing With Possibility, Creativity, And Innovation Within Liminal Spaces, Jennifer Salerno

Doctor of Education

This dissertation aimed to challenge and move beyond unjust social norms related to individual ability and independence, finding such norms based on a fictitious ideal of human capacity. Instead, an ethic of interdependence, such as encompasses the natural world, is defined and promoted in turn. People with disabilities are considered deficient and marginalized because they deviate from ableist norms (Flynn, 2020). They face significant barriers to establishing and maintaining relationships with nature as a result of ability expectations around how bodies should look and behave in the natural world (Wolbring & Lisitza, 2017). People with disabilities covet normality and the …

Interpretable Sample Uncertainty Measures For Ranked-Choice Election Polls, Jason Liang

CMC Senior Theses

Polling results from traditional single-choice plurality elections are readily interpretable. Simple frequentist population parameters are estimated, including each candidate’s total support and the size of the front runner's lead. If the point estimate for the size of the front runner's lead exceeds the margin of error of the lead, we can conclude that the poll shows a statistically significant front runner. However, the interpretability of these population statistics disappears when applied to ranked-choice voting elections. Because ballots rank multiple candidates and candidates are eliminated in rounds, simple population-wide parameters are not well-defined. In RCV elections, a candidate’s ability to win …

When Climate Change Forces Flight: Legal Duties In The Age Of Retreat, Mark P. Nevitt

Faculty Articles

In the face of climate-driven disasters, government officials and individuals alike must decide whether to invest in climate-exposed areas or retreat. This Article analyzes emerging legal and policy issues associated with both climate retreat (when the government relocates people and infrastructure away from climate-exposed areas) and abandonment (when individuals leave climate-exposed areas, following natural disasters or otherwise). I argue that government-driven climate retreat must consider four overlapping legal duties, raising novel questions in an era of climate destabilization. First, does the government have an affirmative duty to rescue its citizens, and is this duty transformed by the government’s role in …

Artificial Intelligence And Consumer Well-Being: A Cross Domain Systemic Review, Setar Lytle, Mahesh Gopinath

Marketing Faculty Publications

Artificial intelligence (AI) is increasingly embedded in everyday consumption, yet evidence on its longer-term implications for consumer eudaimonic well-being remains dispersed across disciplines and application contexts. This review integrates that literature to clarify the domains, theoretical explanations, and conditions through which AI shapes consumer well-being. Following PRISMA and SPAR-4-SLR procedures, we reviewed research published from January 2010 to January 2026. From 6058 records, 480 studies across psychology, business, and human-technology interaction met the inclusion criteria. The evidence is organised through psychological, social, and technological perspectives and identifies six interconnected domains: mental health, cognitive development, physical health, personal growth, autonomy and …

Analyzing Sleep Architecture And Brain State Transitions Via Hidden Markov Models On Fmri Data, Brileigh Jay Cates

Masters Theses

Sleep is associated with systematic changes in brain activity and functional connectivity observable in functional magnetic resonance imagining (fMRI) signals. Because subjects often fall asleep during resting-state experiments, the absence of vigilance monitoring can confound the interpretation of resting-state dynamics. Although electroencephalography (EEG) is the gold standard for sleep staging, simultaneous EEG-fMRI acquisition is not always feasible.

This study investigates whether sleep stages can be inferred directly from fMRI using a probabilistic latent-state framework. Hidden Markov Models (HMMs) are applied to blood-oxygen-level-dependent (BOLD) time series to identify latent brain states and their temporal transitions. Inferred states are aligned with EEG-derived …